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物质使用障碍及药物转移至母乳中的影响:对母婴健康的启示

The Impact of Substance Use Disorder and Drug Transfer into Breast Milk: Implications for Maternal and Infant Health.

作者信息

Yang Yongzong, Yi Bofang, Zhang Tao

机构信息

Meinig School of Biomedical Engineering, Cornell University, 121A Weill Hall, Ithaca, NY 14853, USA.

School of Pharmacy and Pharmaceutical Sciences, SUNY-Binghamton University, 96 Corliss Ave, Johnson City, NY 13790, USA.

出版信息

Pharmaceutics. 2025 May 29;17(6):719. doi: 10.3390/pharmaceutics17060719.

DOI:10.3390/pharmaceutics17060719
PMID:40574032
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12196422/
Abstract

Breast milk provides significant health benefits to both infants and mothers, offering protection against infections and enhancing cognitive development. This paper examines the complex effects of substance use disorder (SUD) during pregnancy and lactation, focusing on the pharmacokinetics of drug transfer into breast milk. It highlights the mechanisms by which drugs enter milk, emphasizing the roles of passive diffusion and active transport, particularly through breast cancer resistance protein (BCRP). The study explores the impact of various substances on fetal and infant health, with a focus on the relative infant dose (RID) and milk-to-plasma (MP) ratio as key metrics for assessing drug safety in breastfeeding. The findings underscore the need for careful evaluation of maternal drug use during lactation to balance the benefits of breastfeeding with potential risks.

摘要

母乳对婴儿和母亲都有显著的健康益处,能预防感染并促进认知发育。本文探讨了孕期和哺乳期物质使用障碍(SUD)的复杂影响,重点关注药物转移至母乳中的药代动力学。它强调了药物进入乳汁的机制,着重阐述了被动扩散和主动转运的作用,尤其是通过乳腺癌耐药蛋白(BCRP)的主动转运。该研究探讨了各种物质对胎儿和婴儿健康的影响,重点将相对婴儿剂量(RID)和乳汁与血浆比值(MP)作为评估母乳喂养中药物安全性的关键指标。研究结果强调,在哺乳期需要仔细评估母亲的药物使用情况,以平衡母乳喂养的益处与潜在风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/def2/12196422/28f8524fdfab/pharmaceutics-17-00719-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/def2/12196422/8e2b253e8d6a/pharmaceutics-17-00719-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/def2/12196422/28f8524fdfab/pharmaceutics-17-00719-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/def2/12196422/8e2b253e8d6a/pharmaceutics-17-00719-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/def2/12196422/28f8524fdfab/pharmaceutics-17-00719-g002.jpg

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本文引用的文献

1
The Effect of Cannabis Consumption During Lactation on the Macronutrient Concentrations in Breast Milk.哺乳期吸食大麻对母乳中常量营养素浓度的影响。
Breastfeed Med. 2025 Jan;20(1):33-41. doi: 10.1089/bfm.2024.0083. Epub 2024 Nov 12.
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A literature review of drug transport mechanisms during lactation.哺乳期药物转运机制的文献综述。
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Exposure to maternal cannabis use disorder and risk of autism spectrum disorder in offspring: A data linkage cohort study.
母亲大麻使用障碍与后代自闭症谱系障碍风险的暴露:一项数据链接队列研究。
Psychiatry Res. 2024 Jul;337:115971. doi: 10.1016/j.psychres.2024.115971. Epub 2024 May 20.
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Human Milk Cannabinoid Concentrations and Associations with Maternal Factors: The Lactation and Cannabis (LAC) Study.人乳中大麻素浓度及其与母体因素的关联:泌乳与大麻(LAC)研究。
Breastfeed Med. 2024 Jul;19(7):515-524. doi: 10.1089/bfm.2024.0021. Epub 2024 May 2.
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Maternal Cannabis Use during Lactation and Potential Effects on Human Milk Composition and Production: A Narrative Review.哺乳期母亲使用大麻及其对母乳成分和分泌量的潜在影响:一项叙述性综述
Adv Nutr. 2024 Apr;15(4):100196. doi: 10.1016/j.advnut.2024.100196. Epub 2024 Mar 1.
6
Predicting Maternal and Infant Tetrahydrocannabinol Exposure in Lactating Cannabis Users: A Physiologically Based Pharmacokinetic Modeling Approach.预测哺乳期大麻使用者母婴四氢大麻酚暴露情况:基于生理药代动力学建模方法
Pharmaceutics. 2023 Oct 14;15(10):2467. doi: 10.3390/pharmaceutics15102467.
7
Academy of Breastfeeding Medicine Clinical Protocol #21: Breastfeeding in the Setting of Substance Use and Substance Use Disorder (Revised 2023).母乳喂养医学会临床方案 21 号:物质使用和物质使用障碍情况下的母乳喂养(2023 年修订)。
Breastfeed Med. 2023 Oct;18(10):715-733. doi: 10.1089/bfm.2023.29256.abm.
8
Cannabidiol Exposure Through Maternal Marijuana Use: Predictions in Breastfed Infants.大麻素通过母体大麻使用的暴露:在母乳喂养婴儿中的预测。
Clin Pharmacokinet. 2023 Nov;62(11):1611-1619. doi: 10.1007/s40262-023-01307-6. Epub 2023 Sep 21.
9
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Hum Exp Toxicol. 2023 Jan-Dec;42:9603271231171643. doi: 10.1177/09603271231171643.
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Physiologically based pharmacokinetic model to predict drug concentrations of breast cancer resistance protein substrates in milk.基于生理的药代动力学模型预测牛奶中乳腺癌耐药蛋白底物的药物浓度。
Biopharm Drug Dispos. 2022 Dec;43(6):221-232. doi: 10.1002/bdd.2335. Epub 2022 Nov 2.